1 code implementation • 12 Jun 2022 • Zongyuan Huang, Shengyuan Xu, Menghan Wang, Hansi Wu, Yanyan Xu, Yaohui Jin
Next location prediction is one decisive task in individual human mobility modeling and is usually viewed as sequence modeling, solved with Markov or RNN-based methods.
no code implementations • 15 Dec 2021 • Huifeng Li, Bin Wang, Sulei Zhu, Yanyan Xu
To address the above challenges, we propose a novel method named SanMove, a self-attention network based model, to predict the next location via capturing the long- and short-term mobility patterns of users.
1 code implementation • 15 Oct 2021 • Huifeng Li, Bin Wang, Fan Xia, Xi Zhai, Sulei Zhu, Yanyan Xu
Targeting this, we propose an end-to-end framework named personalized and group preference guided network (PG$^2$Net), considering the users' preferences to various places at both individual and collective levels.
no code implementations • 8 Oct 2021 • Yuanchao Wang, Wenji Du, ChengHao Cai, Yanyan Xu
The attention mechanism has largely improved the performance of end-to-end speech recognition systems.
1 code implementation • 10 Sep 2021 • Zongyuan Huang, Baohua Zhang, Guoqiang Hu, Longyuan Li, Yanyan Xu, Yaohui Jin
Anomaly detection plays a crucial role in various real-world applications, including healthcare and finance systems.
no code implementations • 6 Aug 2021 • Dengfeng Ke, Yuxing Lu, Xudong Liu, Yanyan Xu, Jing Sun, Cheng-Hao Cai
With the rapid development of neural network architectures and speech processing models, singing voice synthesis with neural networks is becoming the cutting-edge technique of digital music production.
no code implementations • 6 May 2021 • Dengfeng Ke, Jinsong Zhang, Yanlu Xie, Yanyan Xu, Binghuai Lin
With all these modifications, the size of the PHASEN model is shrunk from 33M parameters to 5M parameters, while the performance on VoiceBank+DEMAND is improved to the CSIG score of 4. 30, the PESQ score of 3. 07 and the COVL score of 3. 73.
1 code implementation • 25 Jun 2020 • Yongqiang Dou, Haocheng Yang, Maolin Yang, Yanyan Xu, Dengfeng Ke
Besides, in the experiments, we select three kinds of features that contain both magnitude-based and phase-based information to form complementary and informative features.
no code implementations • 8 Jul 2019 • Wuwei Lan, Yanyan Xu, Bin Zhao
Travel time estimation is a crucial task for not only personal travel scheduling but also city planning.
3 code implementations • 17 Apr 2019 • Feiyang Chen, Ziqian Luo, Yanyan Xu, Dengfeng Ke
Therefore, in this paper, based on audio and text, we consider the task of multimodal sentiment analysis and propose a novel fusion strategy including both multi-feature fusion and multi-modality fusion to improve the accuracy of audio-text sentiment analysis.
Multimodal Emotion Recognition Multimodal Sentiment Analysis
1 code implementation • 28 Oct 2017 • Cheng-Hao Cai, Yanyan Xu, Dengfeng Ke, Kaile Su, Jing Sun
In experiments, it is demonstrated that the revised rules can be used to train a range of functional connections: 20 different functions are applied to neural networks with up to 10 hidden layers, and most of them gain high test accuracies on the MNIST database.
no code implementations • 25 Apr 2017 • Cheng-Hao Cai, Dengfeng Ke, Yanyan Xu, Kaile Su
Briefly, in a reasoning system, a deep feedforward neural network is used to guide rewriting processes after learning from algebraic reasoning examples produced by humans.